Developing the Global Health Cost Consortium Unit Cost Study Repository for HIV and TB: methodology and lessons learned.


Journal

African journal of AIDS research : AJAR
ISSN: 1727-9445
Titre abrégé: Afr J AIDS Res
Pays: South Africa
ID NLM: 101146510

Informations de publication

Date de publication:
Dec 2019
Historique:
entrez: 30 11 2019
pubmed: 30 11 2019
medline: 8 2 2020
Statut: ppublish

Résumé

Consistently defined, accurate, and easily accessible cost data are a valuable resource to inform efficiency analyses, budget preparation, and sustainability planning in global health. The Global Health Cost Consortium (GHCC) designed the Unit Cost Study Repository (UCSR) to be a resource for standardised HIV and TB intervention cost data displayed by key characteristics such as intervention type, country, and target population. To develop the UCSR, the GHCC defined a typology of interventions for each disease; aligned interventions according to the standardised principles, methods, and cost and activity categories from the GHCC Reference Case for Estimating the Costs of Global Health Services and Interventions; completed a systematic literature review; conducted extensive data extraction; performed quality assurance; grappled with complex methodological issues such as the proper approach to the inflation and conversion of costs; developed and implemented a study quality rating system; and designed a web-based user interface that flexibly displays large amounts of data in a user-friendly way. Key lessons learned from the extraction process include the importance of assessing the multiple uses of extracted data; the critical role of standardising definitions (particularly units of measurement); using appropriate classifications of interventions and components of costs; the efficiency derived from programming data checks; and the necessity of extraction quality monitoring by senior analysts. For the web interface, lessons were: understanding the target audiences, including consulting them regarding critical characteristics; designing the display of data in "levels"; and incorporating alert and unique trait descriptions to further clarify differences in the data.

Identifiants

pubmed: 31779571
doi: 10.2989/16085906.2019.1680398
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

263-276

Auteurs

Lori A Bollinger (LA)

Avenir Health, Glastonbury, USA.

Lily Alexander (L)

Department of Global Health, University of Washington, Seattle, USA.

Drew B Cameron (DB)

Department of Health Policy and Management, University of California Berkeley, Berkeley, USA.

Lauren N Carroll (LN)

Philip R Lee Institute for Health Policy Studies, University of California San Francisco, San Francisco, USA.

Lucy Cunnama (L)

Health Economics Unit, University of Cape Town, Observatory, South Africa.

Gabriela B Gomez (GB)

Centre for Health Economics, London School of Hygiene and Tropical Medicine, London, United Kingdom.

Carol Levin (C)

Department of Global Health, University of Washington, Seattle, USA.

Elliot Marseille (E)

Health Strategies International, Oakland, USA.

Mohamed Mustafa Diab (M)

Philip R Lee Institute for Health Policy Studies, University of California San Francisco, San Francisco, USA.

Mariana Siapka (M)

Centre for Health Economics, London School of Hygiene and Tropical Medicine, London, United Kingdom.

Edina Sinanovic (E)

Health Economics Unit, University of Cape Town, Observatory, South Africa.

Anna Vassall (A)

Centre for Health Economics, London School of Hygiene and Tropical Medicine, London, United Kingdom.

James G Kahn (JG)

Philip R Lee Institute for Health Policy Studies, University of California San Francisco, San Francisco, USA.

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Classifications MeSH